Makeflow = Make + Workflow

A workflow can be just a few commands chained together, or it can be a complex application consisting of thousands of tasks. It can have an arbitrary DAG structure and is not limited to specific patterns. Makeflow is used to represent complex applications in fields such as data mining, high energy physics, image processing, and bioinformatics.

Makeflow is portable. A workflow is written in a technology neutral way, and then can be deployed to a variety of different systems without modification, including local execution on a single multicore machine as well as batch systems like HTCondor, SGE, Torque or the bundled Work Queue system. The same specification works for all systems, so you can easily grow your application from one machine up to thousands.

Makeflow differs from other distributed and parallel make tools in that it does not require a distributed filesystem. You can use it to harness whatever machines you have available, and Makeflow handles the data transfer and caching. In addition, Makeflow is highly fault tolerant: it can crash or be killed, and upon resuming, will reconnect to running jobs and continue where it left off by making use of a transaction log.

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Publications

(Showing papers with tag makeflow. See all papers instead.)

Patrick Donnelly and Douglas Thain, Balancing push and pull in Confuga, an active storage cluster file system for scientific workflows, Concurrency and Computation: Practice and Experience, May, 2016. DOI: 10.1002/cpe.3834

Patrick Donnelly, Data Locality Techniques in an Active Cluster Filesystem for Scientific Workflows, Ph.D. Thesis, University of Notre Dame, April, 2016.

Charles Zheng and Douglas Thain, Integrating Containers into Workflows: A Case Study Using Makeflow, Work Queue, and Docker, Workshop on Virtualization Technologies in Distributed Computing (VTDC), June, 2015. DOI: 10.1145/2755979.2755984

Patrick Donnelly, Nicholas Hazekamp, Douglas Thain, Confuga: Scalable Data Intensive Computing for POSIX Workflows, IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, pages 392-401, May, 2015. DOI: 10.1109/CCGrid.2015.95

Dinesh Rajan and Douglas Thain, Designing Self-Tuning Split-Map-Merge Applications for High Cost-Efficiency in the Cloud, IEEE Transactions on Cloud Computing, in press, January, 2015. DOI: 10.1109/TCC.2015.2415780

Olivia Choudhury, Nicholas L. Hazekamp, Douglas Thain, Scott Emrich, Accelerating Comparative Genomics Workflows in a Distributed Environment with Optimized Data Partitioning, C4BIO Workshop at IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), May, 2014.

Nicholas Hazekamp, Olivia Choudhury, Sandra Gesing, Scott Emrich, and Douglas Thain, Poster: Expanding Tasks of Logical Workflows into Independent Workflows for Improved Scalability, IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, pages 548-549, January, 2014. ISBN: 10.1109/CCGrid.2014.84

Casey Robinson and Douglas Thain, Automated Packaging of Bioinformatics Workflows for Portability and Durability Using Makeflow, WORKS13, November, 2013. DOI: 10.1145/2534248.2534258

Peter Bui, A Compiler Toolchain For Data Intensive Scientific Workflows, Ph.D. Thesis, University of Notre Dame, June, 2012.

Michael Albrecht, Patrick Donnelly, Peter Bui, and Douglas Thain, Makeflow: A Portable Abstraction for Data Intensive Computing on Clusters, Clouds, and Grids, Workshop on Scalable Workflow Enactment Engines and Technologies (SWEET) at ACM SIGMOD, May, 2012. DOI: 10.1145/2443416.2443417

Rory Carmichael, Patrick Braga-Henebry, Douglas Thain, and Scott Emrich, Biocompute 2.0: An Improved Collaborative Workspace for Data Intensive Bio-Science., Concurrency and Computation: Practice and Experience, 23(17), pages 2305-2314, December, 2011. DOI: 10.1002/cpe.1782

Peter Bui, Li Yu, Andrew Thrasher, Rory Carmichael, Irena Lanc, Patrick Donnelly, Douglas Thain, Scripting distributed scientific workflows using Weaver, Concurrency and Computation: Practice and Experience, November, 2011. DOI: 10.1002/cpe.1871

Irena Lanc, Peter Bui, Douglas Thain, and Scott Emrich, Adapting Bioinformatics Applications for Heterogeneous Systems: A Case Study, Emerging Computational Methods for the Life Sciences Workshop at ACM HPDC, pages 7-13, June, 2011. DOI: 10.1145/1996023.1996025

Andrew Thrasher, Rory Carmichael, Peter Bui, Li Yu, Douglas Thain, and Scott Emrich, Taming Complex Bioinformatics Workflows with Weaver, Makeflow, and Starch, Workshop on Workflows in Support of Large Scale Science, pages 1-6, November, 2010. DOI: 10.1109/WORKS.2010.5671858

Li Yu, Christopher Moretti, Andrew Thrasher, Scott Emrich, Kenneth Judd, and Douglas Thain, Harnessing Parallelism in Multicore Clusters with the All-Pairs, Wavefront, and Makeflow Abstractions, Journal of Cluster Computing, 13(3), pages 243-256, September, 2010. DOI: 10.1007/s10586-010-0134-7

Douglas Thain and Christopher Moretti, Abstractions for Cloud Computing with Condor, Syed Ahson and Mohammad Ilyas, Cloud Computing and Software Services: Theory and Techniques, pages 153-171, CRC Press, July, 2010. ISBN: 9781439803158

Rory Carmichael, Patrick Braga-Henebry, Douglas Thain, and Scott Emrich, Biocompute: Toward a Collaborative Workspace for Data Intensive Bio-Science, Workshop on Emerging Computational Methods for Life Sciences at ACM HPDC 2010, pages 489-498, June, 2010. DOI: 10.1145/1851476.1851547